A Biomimetic Approach Towards a Dexterous Neuroprosthesis

灵巧神经假体的仿生方法

• 批准号: 10341043
• 负责人: MICHAEL L. BONINGER
• 金额: $ 169.34万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10341043
• 关键词: Activities of Daily Living; Address; Algorithms; Basic Science; Biomimetics; Bypass; Cervical spinal cord injury; Chicago; Chronic; Common Data Element; Development; Devices; Electric Stimulation; Employment Opportunities; Ensure; Esthesia; Eye; Feedback; Fingers; Freedom; Frequencies; Goals; Hand; Hand functions; Human; Hybrids; Institutes; Intuition; Kinetics; Learning; Limb Prosthesis; Limb structure; Longevity; Manuals; Methods; Mind; Motor; Motor Cortex; Movement; Muscle; Neurons; Output; Participant; Pattern; Performance; Persons; Positioning Attribute; Prosthesis; Quadriplegia; Robotics; Scheme; Sensorimotor functions; Sensory; Signal Transduction; Somatosensory Cortex; Spinal cord injury; Tactile; Task Performances; Testing; Tissues; Touch sensation; United States National Institutes of Health; Universities; Work; Wrist; arm; arm function; arm movement; base; brain computer interface; care costs; clinical translation; cost; design; dexterity; experience; grasp; improved; injured; kinematics; limb movement; microstimulation; microsystems; mind control; neuronal patterning; neuroprosthesis; neurotechnology; novel; prosthesis control; prosthetic hand; relating to nervous system; restoration; robot control; sensor; sensory feedback; severe injury; somatosensory; spatiotemporal; success; synergism

PROJECT SUMMARY Cervical spinal cord injury results in the loss of arm and hand function, which significantly limits independence and results in costs over the person’s lifespan. A brain-computer interface (BCI) can be used to bypass the injured tissue to enable control of a robotic arm and to provide somatosensory feedback. Two primary limitations of current state-of-the-art BCIs for arm and hand control are: (1) the inability to control the forces exerted by the prosthetic hand and (2) the lack of somatosensory feedback from the hand. In the proposed study, we seek to considerably improve dexterous control of prosthetic limbs by implementing decoding strategies that enable the user to not only control the movements of the arm and hand, but also the forces transmitted through the hand. We anticipate that our biomimetic approach to decoding will yield intuitive, dexterous control of the prosthetic hand. Tactile sensations will be conveyed to the user through intracortical microstimulation (ICMS) of somatosensory cortex. The spatiotemporal patterns of stimulation will be based on our basic scientific understanding of how tactile information is encoded in somatosensory cortex, which we expect will result in more natural and intuitive sensations. In order to achieve our goal of developing a dexterous neuroprosthesis, we have brought together a team with human BCI experience from the University of Pittsburgh along with the basic science expertise at both Pitt and the University of Chicago. We will collaborate with experts in implantable neurotechnology (Blackrock Microsystems) and robotics (The Biorobotics Institute) to ensure that the device hardware allows us to take a biomimetic approach for control and feedback with an eye toward clinical translation. A total of 4 participants will be tested in a multisite study to accomplish the following three specific aims. Aim 1: Evoke natural and intuitive tactile sensations through ICMS of somatosensory cortex. We expect that biomimetic ICMS will evoke sensations that more closely resemble everyday tactile sensations and intuitively convey information about contacted objects than does standard fixed-frequency ICMS. Aim 2: Derive kinematic and kinetic signals from motor cortex for hand control. We will assess the degree to which motor cortical neurons encode forces exerted on objects. Based on these observations, we will develop hybrid decoders that enable controlling both the movement and force using a synergy-based approach. Aim 3: Demonstrate improved arm and hand function with a biomimetic sensorimotor BCI that combines the sensory feedback developed in Aim 1 with the hybrid decoding developed in Aim 2. A battery of functional assessments will be used including novel metrics designed specifically for sensorimotor prosthetics along with well-established tests identified in the NIH Common Data Elements. We anticipate that subjects will substantially improve their dexterity using a biomimetic BCI as compared to non-biomimetic BCIs or BCIs without somatosensory feedback.

项目摘要 宫颈脊髓损伤导致手臂和手部功能的丧失，这显着限制了独立性 并导致该人的寿命成本。大脑计算机界面（BCI）可用于绕过 受伤的组织可以控制机器人臂并提供体感反馈。两个主要局限性 目前用于手臂和手部控制的最新BCI是：（1）无法控制由 假肢手和（2）缺乏手感反馈。在拟议的研究中，我们试图 通过实施解码策略，可以大大改善对假肢的灵巧控制 用户不仅可以控制手臂和手的运动，还可以控制通过手传递的力。 我们预计我们的仿生方法解码将产生对假肢的直观，灵巧的控制 手。触觉感觉将通过皮质内微刺激（ICM）传达给用户 体感皮质。刺激的时空模式将基于我们的基本科学 了解在体感皮质中如何编码触觉信息的理解，我们期望这会导致更多 自然和直观的感觉。为了实现我们发展灵活的神经假发生的目标，我们已经 从匹兹堡大学购买了一支拥有人类BCI经验的团队以及基本 皮特和芝加哥大学的科学专业知识。我们将与植入专家合作 神经技术（贝莱德微系统）和机器人技术（生物植物学院），以确保设备 硬件使我们能够采用仿生方法来控制和反馈，以注重临床翻译。 在一项多站点研究中将对4个参与者进行测试，以实现以下三个特定目标。目标1： 通过体感皮质的ICM唤起天然和直观的触觉感觉。我们期望那个仿生 ICM会引起感觉，更像每天的触觉并直观地传达 有关接触对象的信息比标准固定频率ICMS。目标2：得出运动学和 来自运动皮层的动力学信号用于手部控制。我们将评估哪种运动皮质神经元的程度 编码在对象上执行的力。基于这些观察结果，我们将开发启用的混合解码器 使用基于协同的方法来控制运动和力。 AIM 3：展示改善的手臂 和手动功能，具有仿生感觉运动BCI，结合了AIM 1中发展的感觉反馈 在AIM 2中开发的混合解码时，将使用一系列功能评估，包括新颖 专为感觉运动假肢设计的指标以及NIH中确定的良好测试 常见数据元素。我们预计受试者将通过仿生型实质上提高其灵巧性 BCI与没有体感反馈的非生物含量BCI或BCI相比。